Metadata-Version: 2.1
Name: xt-models
Version: 0.3.1
Summary: Models and model utilities for common ML tasks
Home-page: https://github.com/XtractTech/xt-models
Author: Xtract AI
Author-email: info@xtract.ai
License: UNKNOWN
Description: # xt-models
          
        ## Description
        
        This repo contains common models and utilities for working with ML tasks, developed by [Xtract AI](https://xtract.ai/).
        
        
        
        More to come.
        
        ## Installation
        From PyPi:
        ```bash
        pip install xt-models
        ```
        
        From source:
        ```bash
        git clone https://github.com/XtractTech/xt-models.git
        pip install ./xt-models
        ```
        
        ## Usage
        
        
        #### Grabbing a segmentation model
        
        ```python
        from xt_models.models import ModelBuilder, SegmentationModule
        from torch import nn
        
        deep_sup_scale = 0.4
        fc_dim = 2048
        n_class = 2
        net_encoder = ModelBuilder.build_encoder(
            arch="resnet50dilated",
            fc_dim=fc_dim,
            weights="/nasty/scratch/common/smart_objects/model/ade20k/encoder_epoch_20.pth"
        )
        net_decoder = ModelBuilder.build_decoder(
            arch="ppm_deepsup",
            fc_dim=fc_dim,
            num_class=150,
            weights="/nasty/scratch/common/smart_objects/model/ade20k/decoder_epoch_20.pth"
        )
        in_channels = net_decoder.conv_last[-1].in_channels
        net_decoder.conv_last[-1] = nn.Conv2d(in_channels, n_class, kernel_size=(1, 1), stride=(1, 1))
        net_decoder.conv_last_deepsup = nn.Conv2d(in_channels, n_class, 1, 1, 0)
        
        
        model = SegmentationModule(net_encoder, net_decoder, deep_sup_scale)
        ```
        
        #### Grabbing a detection model
        
        ```
        from xt_models.models import Model
        
        model_cfg = "./xt_models/models/object_detection/yolov5x.yaml"
        model = Model(model_cfg)
        ```
        #### Implementing a new model
        
        If you are having to always copy and paste the same model code for different projects, simply add the model code to the `models` directory, and import it in the `models/__init__.py` file.
        
        ## Data Sources
        
        [descriptions and links to data]
          
        ## Dependencies/Licensing
        
        [list of dependencies and their licenses, including data]
        
        ## References
        
        [list of references]
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Provides: xt_models
Description-Content-Type: text/markdown
